Run
5985594

Run 5985594

Task 23 (Supervised Classification) cmc Uploaded 17-07-2017 by Jan van Rijn
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  • openml-pimp openml-python Sklearn_0.18.1.
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Flow

sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.Conditiona lImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethres hold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classif ier=sklearn.ensemble.forest.RandomForestClassifier)(1)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(21)_bootstrapfalse
sklearn.ensemble.forest.RandomForestClassifier(21)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(21)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(21)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(21)_max_features0.1343899751224482
sklearn.ensemble.forest.RandomForestClassifier(21)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(21)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(21)_min_samples_leaf4
sklearn.ensemble.forest.RandomForestClassifier(21)_min_samples_split16
sklearn.ensemble.forest.RandomForestClassifier(21)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(21)_n_estimators100
sklearn.ensemble.forest.RandomForestClassifier(21)_n_jobs1
sklearn.ensemble.forest.RandomForestClassifier(21)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(21)_random_state60083
sklearn.ensemble.forest.RandomForestClassifier(21)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(21)_warm_startfalse
openmlstudy14.preprocessing.ConditionalImputer(2)_axis0
openmlstudy14.preprocessing.ConditionalImputer(2)_categorical_features[1, 2, 4, 5, 6, 7, 8]
openmlstudy14.preprocessing.ConditionalImputer(2)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(2)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(2)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_verbose0
sklearn.preprocessing.data.OneHotEncoder(7)_categorical_features[1, 2, 4, 5, 6, 7, 8]
sklearn.preprocessing.data.OneHotEncoder(7)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(7)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(7)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(7)_sparsefalse
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold0.0

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

17 Evaluation measures

0.7258 ± 0.0326
Per class
Cross-validation details (10-fold Crossvalidation)
0.5294 ± 0.0287
Per class
Cross-validation details (10-fold Crossvalidation)
0.2694 ± 0.0429
Cross-validation details (10-fold Crossvalidation)
279.0196 ± 3.3459
Cross-validation details (10-fold Crossvalidation)
0.3781 ± 0.0081
Cross-validation details (10-fold Crossvalidation)
0.4308 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
1473
Per class
Cross-validation details (10-fold Crossvalidation)
0.5289 ± 0.0296
Per class
Cross-validation details (10-fold Crossvalidation)
0.537 ± 0.0268
Cross-validation details (10-fold Crossvalidation)
1.5392
Cross-validation details (10-fold Crossvalidation)
0.537 ± 0.0268
Per class
Cross-validation details (10-fold Crossvalidation)
0.8776 ± 0.0189
Cross-validation details (10-fold Crossvalidation)
0.4641 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
0.4299 ± 0.0092
Cross-validation details (10-fold Crossvalidation)
0.9262 ± 0.02
Cross-validation details (10-fold Crossvalidation)